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Class library written in C++ which implements neural networks

OpenNN is a class library written in C++ which implements neural networks.

The library is intended for advanced users, with high C++ and machine learning skills. OpenNN provides an effective framework for the research and development of data mining and predictive analytics algorithms and applications.

OpenNN is based on the most popular neural network model, the multilayer perceptron. The package comes with unit testing, many examples and extensive documentation.

The library has been designed to learn from data sets. Some typical applications here are function regression (modelling), pattern recognition (classification) and time series prediction (forecasting).

OpenNN is being developed by Intelnics, a company specialized in the development and application of neural networks.



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25 November 2014


License is written in a PDF file included in the download.

Leaders and contributors

Roberto Lopez Author

Resources and communication

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Software prerequisites


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Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.3 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. A copy of the license is included in the page “GNU Free Documentation License”.

The copyright and license notices on this page only apply to the text on this page. Any software or copyright-licenses or other similar notices described in this text has its own copyright notice and license, which can usually be found in the distribution or license text itself.